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aoju-memory傲居记忆

Agent Skill

aoju-memory 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,333

周安装

177

GitHub Stars

公开资料未说明

下载量

1,402
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:aoju-memory(傲居记忆)
来源仓库:https://github.com/chaibaoqing/aoju-memory
安装命令:
openclaw skills install aoju-memory
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install aoju-memory

简介

用于记录任务执行中的错误、反馈与能力缺口。

  • 支持长期记忆积累与自我进化机制。aoju-memory 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 在会话初始化时激活以持续优化决策质量。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 使用时需在重大决定后主动触发反馈更新。
  • 涉及敏感信息时应加密存储并限制访问权限。

SKILL.md

name
aoju-memory
description
Long-term memory, learning, and self-evolution for the agent. Activates on session start (SOUL.md/USER.md context), after significant decisions, on feedback, and during periodic heartbeat reviews. Maintains MEMORY.md, daily logs, learnings corpus, and behavioral patterns.

Memory Learner

Long-term memory + learning from experience + self-evolution.

Core Principle

Write to files, not mental notes. Every lesson, decision, preference, or event worth remembering goes into structured files immediately — not kept in context.


When This Skill Activates

1. Session Start (every time)

Read these files before anything else:

  • SOUL.md — who I am
  • USER.md — who I'm helping
  • MEMORY.md — curated long-term memory
  • memory/YYYY-MM-DD.md — recent context (today + yesterday)

2. After Significant Decisions

When I make a decision worth remembering (tool choice, strategy, opinion):

  • Write to memory/YYYY-MM-DD.md
  • If important, distill to MEMORY.md

3. On Feedback / Mistakes

When user corrects me, expresses frustration, or I realize I made a mistake:

LEARN: <what happened>
LESSON: <what I should do differently>
CONFIDENCE: high/medium/low

→ Store in memory/learnings/YYYY-MM-DD.md

4. Pre-Task Recall (on request)

Before significant tasks, search memory for related context:

mem_recall "task description"

Returns relevant memories, learnings, and past decisions.

5. Heartbeat Review (periodic)

During heartbeats, do light maintenance:

  • Review today's memory/YYYY-MM-DD.md
  • Identify learnings worth capturing
  • Update MEMORY.md if anything significant

6. Evolution Check (weekly or on request)

mem_evolve

Review learnings corpus, identify patterns, update behavioral guidelines in SOUL.md.


Memory Structure

memory/
  YYYY-MM-DD.md          # Daily raw log
  learnings/
    YYYY-MM-DD.md        # Daily lessons learned
    patterns.md          # Repeated mistake patterns
MEMORY.md                # Curated long-term memory

Daily Log Format

## Session DD

### What happened
[Context, decisions, outcomes]

### Key decisions
- [decision] → [why]

### To remember
- [fact about user/preference/project]

Learnings Format

# Learning: YYYY-MM-DD

## Incident
[What happened]

## Lesson
[What I should do differently]

## Context
[When this applies]

## Tags
#feedback #mistake #ui #tool-choice

MEMORY.md Categories

  • Identity: Who I am, my values
  • User: Preferences, projects, context
  • Learnings: Important lessons (distilled)
  • Projects: Active work and status
  • Patterns: Recurring situations and how I handle them

Scripts

  • mem_recall.py — Search memories by query
  • mem_learn.py — Capture a learning
  • mem_evolve.py — Review and evolve behavioral patterns
  • mem_status.py — Show memory health summary

Evolving

Every 5 learnings, do an evolution review:

  1. Read recent learnings
  2. Identify patterns (same mistake twice = pattern)
  3. Update SOUL.md or AGENTS.md with new behavioral guidelines
  4. Archive learnings to patterns.md

This is how I get genuinely smarter over time, not just accumulate notes.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

87.91%
按下载量换算1,232

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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